coinranking-automation
by ComposioHQcoinranking-automation helps agents run Coinranking workflow automation through Composio Rube MCP by discovering live tool schemas, checking the Coinranking connection, and executing supported crypto data tasks.
This skill scores 66/100, which makes it acceptable for listing but limited. Directory users get enough evidence to understand that it is a Rube MCP-based Coinranking automation skill and how an agent should begin using it, but they should expect a thin wrapper around tool discovery rather than a rich, self-contained workflow library.
- Valid skill frontmatter clearly names the trigger domain and requires the Rube MCP dependency.
- Prerequisites and setup explain that users need RUBE_SEARCH_TOOLS and an active Coinranking connection via RUBE_MANAGE_CONNECTIONS.
- The workflow pattern explicitly instructs agents to discover current tool schemas before execution, reducing risk from stale Coinranking tool definitions.
- No support files, scripts, references, or README are included beyond SKILL.md, so adoption depends entirely on the short inline instructions.
- It delegates most operational detail to live RUBE_SEARCH_TOOLS discovery rather than documenting concrete Coinranking task examples or schemas.
Overview of coinranking-automation skill
What coinranking-automation does
coinranking-automation is a Claude skill for running Coinranking workflows through Composio’s Rube MCP server. It helps an agent discover current Coinranking tool schemas, check the required connection, and execute cryptocurrency data tasks without hard-coding stale API shapes.
The core value is not “ask about crypto prices” in a generic way. The skill is designed to make the agent use RUBE_SEARCH_TOOLS first, then choose the right Coinranking tool from the live Rube MCP catalog before taking action.
Best fit for workflow automation users
This coinranking-automation skill is a good fit if you want an AI agent to automate repeatable Coinranking tasks such as retrieving coin data, market information, rankings, or other supported Coinranking toolkit operations through Composio.
It is especially useful for users building research, reporting, monitoring, or data-enrichment workflows where the agent must call tools rather than invent answers from model memory.
What makes it different from a normal prompt
A normal prompt might ask the model to “get Coinranking data,” but the model may not know the current tool names, required fields, or authentication state. coinranking-automation adds an execution pattern: discover tools, confirm the Coinranking connection, inspect schemas, then run the selected operation.
That pattern matters because MCP tool schemas can change. The skill explicitly instructs the agent to search tools first instead of relying on outdated assumptions.
Key adoption requirement
The main blocker is MCP setup. The skill requires Rube MCP with RUBE_SEARCH_TOOLS available and an active Coinranking connection managed through RUBE_MANAGE_CONNECTIONS. If you do not plan to use Rube MCP or Composio’s Coinranking toolkit, this skill will not provide much value.
How to Use coinranking-automation skill
coinranking-automation install context
Install the skill from the Composio skills repository using your preferred Claude skills workflow. In environments that support the common skills installer, the command is typically:
npx skills add ComposioHQ/awesome-claude-skills --skill coinranking-automation
Then add Rube MCP to your client configuration using:
https://rube.app/mcp
After MCP is connected, verify that RUBE_SEARCH_TOOLS responds. Next, call RUBE_MANAGE_CONNECTIONS with toolkit coinranking and complete the returned authorization flow if the connection is not ACTIVE.
Inputs the skill needs from you
For strong coinranking-automation usage, give the agent the actual business goal, the target asset or market scope, the desired fields, freshness expectations, and output format. Avoid vague requests such as “check crypto data.”
A stronger prompt looks like:
Use coinranking-automation for Workflow Automation. Discover the current Coinranking tools first. I need the latest ranking and market data for Bitcoin and Ethereum, including price, market cap, 24h change, and rank. Return a compact table and note any fields that the current tool schema does not support.
This gives the agent enough context to search for the right Coinranking operation and map the result into the desired format.
Practical workflow to follow
Start every workflow with tool discovery:
RUBE_SEARCH_TOOLS with a use case such as "get latest Coinranking price and market data for BTC and ETH".
Then check the Coinranking connection with RUBE_MANAGE_CONNECTIONS. If the connection is inactive, complete authentication before attempting any data call. Once the available tool slug and schema are known, run the tool with only supported fields.
For multi-step automations, reuse the MCP session where possible. Ask the agent to summarize the selected tool name, required inputs, and any schema limitations before execution if the workflow will affect downstream reports or dashboards.
Repository files to read first
The repository path is composio-skills/coinranking-automation, and the main file to inspect is SKILL.md. There are no extra scripts/, resources/, references/, or rules/ folders in the provided structure, so the skill’s behavior is concentrated in that file.
Read these sections first: Prerequisites, Setup, Tool Discovery, and Core Workflow Pattern. They explain the real operating contract: Rube MCP must be connected, Coinranking auth must be active, and tool schemas must be discovered at runtime.
coinranking-automation skill FAQ
Is coinranking-automation a crypto trading bot?
No. coinranking-automation is an automation skill for accessing Coinranking operations through Rube MCP. It can support market-data workflows, reporting, and research tasks, but it does not provide trading strategy, exchange execution, portfolio custody, or financial advice by itself.
Can beginners use this skill?
Yes, if they are comfortable configuring MCP connections. The Coinranking side is simplified through Composio/Rube, but you still need to add the MCP server, confirm RUBE_SEARCH_TOOLS works, and activate the coinranking connection. Users who only want a chat answer with no tool setup may find it heavier than necessary.
Why must the agent search tools first?
The skill’s most important rule is to call RUBE_SEARCH_TOOLS before execution. This prevents failures caused by outdated tool names, missing required fields, or changed schemas. It also lets the agent discover recommended execution plans and pitfalls from the live Rube MCP catalog.
When should I not use this skill?
Do not use the coinranking-automation skill if you cannot connect Rube MCP, if you need a direct Coinranking API client in your own codebase, or if your task requires guaranteed real-time trading-grade data. It is best for agent-driven workflow automation, not low-latency market infrastructure.
How to Improve coinranking-automation skill
Improve prompts for coinranking-automation
Better prompts produce better tool choices. Include the coin symbols, identifiers, date or freshness requirements, fields needed, output format, and downstream use.
Weak:
Get coin data.
Stronger:
Use coinranking-automation. Search current Coinranking tools first, then retrieve current data for BTC, ETH, and SOL. Include rank, price, market cap, 24h percentage change, and source timestamp if available. Return JSON for ingestion into an automation workflow.
The stronger version reduces guesswork and helps the agent reject unsupported fields cleanly.
Reduce common failure modes
The most common failure is trying to call a Coinranking tool before discovery or before the connection is active. Make the agent explicitly confirm both steps: RUBE_SEARCH_TOOLS responds, and RUBE_MANAGE_CONNECTIONS shows toolkit coinranking as ACTIVE.
Another common issue is asking for fields that the discovered schema does not expose. Tell the agent to report unsupported fields instead of fabricating values.
Iterate after the first output
After the first run, ask for a short execution note: selected tool slug, input parameters used, omitted fields, and any schema constraints. This makes the workflow easier to debug and repeat.
If the output will feed reports or alerts, refine the prompt with sorting rules, numeric formatting, missing-data handling, and whether the agent should return raw tool output, a table, or normalized JSON.
Add local guardrails around the skill
For production-style workflow automation, wrap coinranking-automation with your own validation rules. Examples include allowed coin lists, required output schema, maximum number of assets per call, retry behavior, and a rule that no financial recommendations should be generated from raw market data unless a separate review step exists.